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Api Python Jobs in New York, NY (NOW HIRING)

Apex Informatics

Python Developer

Jersey City, NJ · On-site

$55 - $75.75/hr

Python + React + Rest APi Position will be of Senior Python Developer who has experience working in Python, REST, ReactJS and Preferably experience working in Financial services within Global Markets ...

My3Tech Inc

API Engineer

Roseland, NJ · On-site

ADP is looking for a senior Python API engineer. -AWS preferred but any cloud experience -senior in API development Plus: working with genAI or graphQL Required Skills : senior python api developer ...

Jobsbridge

Python Engineer

New York, NY

... Python/Django - Strong object-oriented programming background - Experience creating REST ... API's - Understanding of working in a Linux environment - Ability to work within a MySQL/NoSQL ...

E-Solutions, Inc.

Python Developer

Manhattan, NY · On-site +1

$55.50 - $76.25/hr

Python Developer Experience (only number of years): 5 Salary: As per industry standards Roles and ... Solid understanding of RESTful API development and integration * Familiarity with front-end ...

New

Skywaves MP LLC

Python Developer

Manhattan, NY

$55.50 - $76.25/hr

We are seeking a Senior Python Backend-Heavy Full Stack AI Engineer with hands-on experience in ... API design & production system experience AI / Agentic Frameworks (Critical) • Hands-on ...

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How much do api python jobs pay per hour?

As of May 28, 2026, the average hourly pay for api python in New York, NY is $64.13, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $72.84 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an API Python Developer, and why are they important?

To thrive as an API Python Developer, you need a solid understanding of Python programming, RESTful API design, and experience with frameworks like Flask or Django, often supported by a degree in computer science or related field. Familiarity with version control systems like Git, API testing tools such as Postman, and containerization platforms like Docker is commonly required. Strong problem-solving abilities, attention to detail, and effective communication skills set top developers apart. These skills ensure robust, secure, and scalable API solutions that meet business requirements and facilitate seamless collaboration within development teams.

What are some common challenges faced by API Python developers when integrating third-party services, and how can they be addressed?

API Python developers often encounter challenges such as inconsistent documentation, rate limiting, and unexpected changes in third-party APIs. To address these, it's important to thoroughly read and test API documentation, implement robust error handling and retry logic, and use environment variables or configuration files to manage sensitive credentials. Developers should also stay updated on API version changes and participate in relevant developer communities to share solutions and best practices.

What is an API Python developer?

An API Python developer is a software professional who specializes in creating, implementing, and maintaining Application Programming Interfaces (APIs) using the Python programming language. Their main responsibilities include designing RESTful or GraphQL APIs, integrating third-party services, ensuring secure and efficient data exchange, and writing clean, scalable code. API Python developers often work closely with front-end developers and other back-end engineers to support seamless communication between different parts of a software system.

Can Python make API calls?

Python can make API calls using libraries such as requests or http.client, which allow developers to send HTTP requests and handle responses. As an API developer or Python programmer, understanding how to work with these libraries is essential for integrating external services or data sources into applications.

What is the difference between Api Python vs Data Analyst?

AspectApi PythonData Analyst
Required SkillsPython programming, API integration, data manipulationData visualization, statistical analysis, Excel, SQL
Work EnvironmentSoftware development, backend services, data pipelinesBusiness insights, reporting, data interpretation
Common EmployersTech companies, startups, data-driven organizationsFinance, marketing, consulting firms

Api Python focuses on developing and maintaining APIs using Python, emphasizing coding and technical skills. Data Analysts interpret data to provide business insights, often using tools like Excel and SQL. While Api Python roles are more technical and development-oriented, Data Analysts focus on analyzing data to support decision-making. Both roles may overlap in data handling but serve different primary functions within organizations.

What are popular job titles related to Api Python jobs in New York, NY? For Api Python jobs in New York, NY, the most frequently searched job titles are:
What job categories do people searching Api Python jobs in New York, NY look for? The top searched job categories for Api Python jobs in New York, NY are:
What cities near New York, NY are hiring for Api Python jobs? Cities near New York, NY with the most Api Python job openings:
Api Python jobs near you

Principal Engineer - Python API Development

Fidelity Investments

Jersey City, NJ • On-site

$107K/yr

Full-time

Medical, Retirement, PTO

Posted 12 hours ago

Fidelity Investments rating

8.7

Company rating: 8.7 out of 10

Based on 264 frontline employees who took The Breakroom Quiz

14th of 138 rated financial services

Job description

Job Description:
Note: Fidelity will not provide immigration sponsorship for this position.
Principal Engineer - Python API Development
The Role:
As a Principal Engineer on the Enterprise AI/ML Platform team, you will tackle the most complex technical challenges involved in delivering machine learning at enterprise scale. You will design, build, and evolve reliable, secure, and cost-efficient platform capabilities-from model packaging and serving to observability and lifecycle management-working closely with multiple teams to ensure these capabilities are practical, robust, and widely usable in production.
You will take a hands-on role across enterprise repositories, improving shared services, CI/CD workflows, and infrastructure patterns where they have the greatest impact. This includes deep technical investigation of performance and scalability issues, such as tracking down bottlenecks in web services, analyzing system and application metrics, and optimizing GPU utilization, throughput, and resource efficiency across ML workloads.
The Expertise & Skills You Bring
  • Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline; 8+ years (typically 10+) building and operating production platforms and services at scale.
  • Deep software engineering expertise in Python and distributed systems, with a track record of building production-grade services, libraries, and internal platforms. You model engineering excellence through clean designs, automated testing, and maintainable abstractions; Linux fluency and scripting are required.
  • Familiarity with Java or Groovy is a plus.
  • Knowledge or experience with GenAI Gateways or LiteLLM a big plus.
  • Cloud platform leadership (AWS)-hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS-and experience shaping platform patterns that other teams adopt. Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial.
  • DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git-based workflows), containerization (Docker), release governance, and multi-environment promotion for ML-enabled workloads.
  • Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post-mortems) for ML serving and data/feature pipelines.
  • ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use-without a research or modeling focus.
  • Cross-org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes.
  • Set platform strategy and standards for ML packaging, deployment, serving, and observability-driving consistent adoption across squads and business units.
  • Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production.
  • Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services.
  • Advance model/data observability-tooling for data and feature drift detection, prediction-quality monitoring and uncertainty signals, and automated diagnostics/ explainability.
  • Lead cross-platform incident response and post-mortems, drive systemic fixes, and evolve standards to prevent recurrence-across applications and the platform.
  • Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale.
  • Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long-term platform roadmap.

The Team
The Enterprise Data Science Platform, part of the Fidelity Data Architecture team within the Enterprise Technology business unit, is responsible for delivering scalable AI/ML capabilities across the organization. The team designs and builds advanced cloud-based, open-source, software platforms in close collaboration with Data Scientists, enabling the efficient packaging, deployment, and operation of AI/ML models at production scale.
In addition, the platform develops and maintains enterprise-grade gateways that allow teams across the company to securely discover, access, and consume AI/ML models. These gateways provide critical visibility into model usage and costs, while generating insights into model effectiveness, adoption patterns, and opportunities for continuous improvement.
The base salary range for this position is $107,000-216,000 USD per year.
Placement in the range will vary based on job responsibilities and scope, geographic location, candidate's relevant experience, and other factors.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.
We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career. Note, the application window closes when the position is filled or unposted.
Please be advised that Fidelity's business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.
Certifications:
Category:
Information Technology

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